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Hear The Flow: Optical Flow-Based Self-Supervised Visual Sound Source Localization

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Learning to localize the sound source in videos without explicit annotations is a novel area of audio-visual research. Existing work in this area focuses on creating attention maps to capture the correlation between the two modalities to localize the source of the sound. In a video, oftentimes, the objects exhibiting movement are the ones generating the sound. In this work, we capture this characteristic by modeling the optical flow in a video as a prior to better aid in localizing the sound source. We further demonstrate that the addition of flow-based attention substantially improves visual sound source localization. Finally, we benchmark our method on standard sound source localization datasets and achieve state-of-the-art performance on the Soundnet Flickr and VGG Sound Source datasets. Code: https://github.com/denfed/heartheflow.

Dennis Fedorishin, Deen Dayal Mohan, Bhavin Jawade, Srirangaraj Setlur, Venu Govindaraju• 2022

Related benchmarks

TaskDatasetResultRank
Sound Source LocalizationFlickr SoundNet (test)
CIoU84.8
28
Audio referred image groundingPascalSound (test)
cIoU55.48
10
Audio referred image groundingAVSBench (test)
cIoU67.49
10
Audio referred image groundingVGG-SS (test)
cIoU39.4
10
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